AGCI research programme: Ecology and Ecosystem Service Assessment

AGCI postdoc: Matthew Helmus

This postdoc project aims to develop a statistical framework that can be used on experimental and field survey data sets to estimate the levels and aspects of biodiversity needed to maintain ecosystem services in the face of global change. The focus will be on multilevel models which are regressions where the parameters are given probability models with their own estimated parameters. Multilevel models are more informative than standard regression models because they are flexible, provide intuitive variance partitioning, and can be used to make robust predictions of complicated processes. This project proposes to develop a suite of multilevel statistical techniques, based on generalized linear mixed models, that can be used on a variety of ecosystem service data sets to: 1) estimate the biodiversity aspects that best provide an ecosystem service (e.g., which species with which trait combinations); 2) predict the effects of an understudied species on ecosystem services based on the known traits of close relatives; and 3) predict how ecosystem services will be altered as species and traits are lost or gained from ecosystems as global change proceeds.

Short CV

Matt is a post-doctoral researcher at the Amsterdam Global Change Institute (AGCI). His undergraduate research was on how monarch butterfly caterpillars avoided the defenses of their host plants, milkweeds. While in graduate school he worked on fish and aquatic insects of the lakes of northern Wisconsin, USA and the rivers of central Mexico. His main PhD research focused on using evolutionary history to explain patterns of ecological community structure. After his PhD, he worked in China and at the University of Chicago where he continued to work on evolutionary approaches to community ecology and extended his research into genomics.